Guides
Practical how-to content for platform engineers and AI teams — routing strategy, compliance, budget management, evals, and self-hosted deployment.
Rolling out per-team LLM budgets
Configure spend limits, alert thresholds, and hard caps per team using ManyLayers Gateway's budget engine — without touching application code.
Choosing a routing strategy
Latency-first, cost-first, or quality-first? A decision framework for configuring single, fallback, canary, and conditional routing across 40+ providers.
Building a PII-safe prompting program
How to deploy ManyLayers Gateway's PII firewall across your organization — redaction modes, allow-list patterns, and audit logging without storing sensitive data.
Connecting your knowledge sources
A practical overview of ManyLayers Workspace connectors — how to ingest documents, databases, and SaaS tools into your knowledge base for RAG-powered AI workflows.
Running evals your team will trust
Set up ELO-ranked model comparisons, golden datasets, and continuous eval scoring in ManyLayers Workspace — fed from real gateway traffic during canary rollouts.
Going air-gapped: a self-hosting checklist
Everything your team needs to deploy ManyLayers in a fully isolated environment — network requirements, license activation, model weight distribution, and operational readiness.